Walking through a run of WordCount

To explore the relationship between mapper and reducer in more detail, and to expose some of Hadoop's inner working, we'll now go through just how WordCount (or indeed any MapReduce job) is executed.


The call to Job.waitForCompletion() in the driver is where all the action starts. The driver is the only piece of code that runs on our local machine, and this call starts the communication with the JobTracker. Remember that the JobTracker is responsible for all aspects of job scheduling and execution, so it becomes our primary interface when performing any task related to job management. The JobTracker communicates with the NameNode on our behalf and manages all interactions relating to the data stored on ...

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